AI Engineer

At Leidos youll contribute to AI solutions that serve critical national and global missionsranging from defense and intelligence to healthcare energy and space exploration. Our work emphasizes Trusted Mission AI: systems that are transparent ethical resilient and accountable. Youll collaborate with multidisciplinary teams to transition AI research into operational environments where accuracy security and reliability are non-negotiable. Joining Leidos means applying your expertise to solve some of the most complex and meaningful challenges of our time.

We are looking for a motivated AI engineer who wants to work on challenging problems in a variety of domains including enterprise IT health defense intelligence and energy to get results that apply and go beyond the state of the art for measurably better outcomes.

We apply our knowledge capabilities and experience to develop and deploy Trusted Mission AI AI that deserves to be trusted by system owners end users and the public to be helpful harmless and honest. We are looking for a researcher that is expert in envisioning developing and securing AI agents using generative AI and LLM-based tools to transform and add value to human workflows.

Primary Responsibilities

The AI Engineer will collaborate with Agentic AI Scientists to build and deploy AI agents to both automate and optimize labor intensive workflows as well as empowering the human workforce to discover entirely new capabilities. As a member of the Leidos AI Accelerator they will be tasked at different times with both R&D as well as customer-facing goals to speed the transition of novel applied research and solutions development into impact on contract.

The tasks of the AI Engineer will include creating software to support AI agent communication connecting models and agents to external services via API calls testing and debugging tasks deploying into target environments setting up monitoring and ensuring reliable execution of agentic AI systems. They will utilize a combination of open-source models agentic tools and large proprietary commercial models. They will be developing novel approaches to securing agentic workflows and to evaluating the results for accuracy performance and impact. They will be expected to ensure AI systems adhere to ethical guidelines transparency and fairness principles. They should expect they may conduct research develop prototypes evaluate and document results potentially through publication and presentation at conferences and other public forums. They should also expect they may be part of a team developing solutions for deployment into operational environments or for integration into mission systems. They should be a self-starter while also working well within the team collaborating and sharing discoveries and seeking feedback.

Multiple openings at various levels. The various positions minimum education and experience requirements are as follows:

• T1: Bachelors degree in Computer Science Engineering or related field and relevant experience
• T2: Bachelors degree in Computer Science Engineering or related field and 2 years of relevant experience or a Masters degree with relevant experience
• T3: Bachelors degree in Computer Science Engineering or related field and 4 years of directly applicable experience or a Masters degree and 2 years of directly applicable experience

Basic Qualifications

• Self-starter with a high degree of intellectual curiosity
• Proficiency in applying technical principles theories and concepts in the field
• Experience developing Agentic AI solutions including autonomous planningexecutionreflection loops multi-agent collaboration and coordination and tool usage patterns including API integration retrieval-augmented generation (RAG) and memory/context management
• Solid understanding and hands-on experience with generative AI models including prompt engineering chain-of-thought reasoning and Natural Language Processing (NLP) tasks such as entity extraction summarization and semantic search.
• Ability to effectively guide junior engineers in applying standard practices and resolving problems of moderate complexity
• Working knowledge of Large Language Models (LLMs) and agent frameworks such as LangChain LangGraph CrewAI A2A MCP or AutoGen
• Experience using vector databases (e.g. Pinecone Weaviate FAISS)
• Proficiency in modern software languagespreferably Python
• Experience with the Software Development Lifecycle (SDLC) including DevSecOps practices
• Familiarity with deployment into virtualized and containerized environments (e.g. VMware Docker Kubernetes)
• Ability to obtain a Secret clearance

Preferred Qualifications

• Experience designing and implementing safety guardrails and bias-mitigation strategies for autonomous agents and multiagent systems
• Experience integrating agents with cloud-native workflows streaming data pipelines and real-time decision-making environments
• Familiarity with evaluation and observability tools for AI agents such as LangSmith OpenAI Evals or custom telemetry systems
• Experience with AI service integration such as NIMS Azure OpenAI Bedrock GCP Vertex AI
• Proficiency in scripting with Linux Bash PowerShell or equivalent automation tools
• Hands-on GPU programming experience for ML workloads using CUDA PyTorch or TensorFlow including optimization for performance and efficiency.

If youre looking for comfort keep scrolling. At Leidos we outthink outbuild and outpace the status quo because the mission demands it. Were not hiring followers. Were recruiting the ones who disrupt provoke and refuse to fail. Step 10 is ancient history. Were already at step 30 and moving faster than anyone else dares.

Original Posting:

Pay Range:

The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job education experience knowledge skills and abilities as well as internal equity alignment with market data applicable bargaining agreement (if any) or other law.